Introducing results from micro-simulation models on shared - PowerPoint PPT Presentation

Introducing results from micro-simulation models on shared mobilityfor cities (Helsinki, Auckland, Dublin, Lisbon and Lyon) into the ITF urban passenger model Luis Martinez (with Olga Petrik, Francisco Furtado and Jari Kauppila) ITEM4 Workshop, IIASA, Laxenburg, Austria

What is the shared mobility concept we are exploring? Not ot c current nt TN TNC’ C’s sol solut utio ion… n…

Sharedmodes specification Mode Booking Access time Max. waiting Max. total time loss Vehicle type time (depending (depending on on distance) distance) Shared Real Door-to-door 5 minutes Detour time + waiting Minivan of 8 (≤ 3 km), up to Taxi time time, from 7 minutes seats rearranged (≤3 km), up to 10 minutes for 6 seats, with (≥ 12 km) 15 minutes (≥12 km) easy entry/exit Taxi- 30 Boarding and alighting Tolerance of Minimum linear speed Minibuses with Bus minutes up to 400 m away 10 minutes from from origin to 8 and 16 seats. in from door, at points preferred destination (15 km/h) No standing advance designated in real time boarding time places Shared Taxis Taxi-Bus simultaneous ride-sharing optimised on-demand bus

Sharedmodes specification Max. waiting time Max. total time Mode Booking Access time (depending on loss (depending Vehicle type distance) on distance) 10 minutes access (walking or 15 to 30 Walk to a carpooling Tolerance of 15 driving) + five Regular private Platform minutes stop or drive to a minutes from extra minutes car (owner by the in carpooling dedicated preferred departure waiting at stop or carpooling assigned driver) advance parking lot time depot + 10 minutes walking at destination Platform carpool centralised private carpool dispatched

Qualitative comparison of transport modes Service quality Service type On-board Assessing the range of quality Access Waiting Transfers Comfort Price time Private Car of specification designed for shared mobility services Public transport New services may emerge in and/ or this spectrum Shared Taxi (e.g. peer to peer ridesharing) Taxi-Bus Feeder service to Legend: rail, ferry or BRT Comparative modes performance rating + Very low performance Low performance Carpooling Average performance High performance Very high performance

How to assess it?

Modellin llingFramew ewor ork Characterisation Mobility seed and transport Synthetic mobility dataset mode preferences of the study area Modeling Fram ew ork Household characterisation Travel survey (Residential location, Transport Mode choice model family profile) infrastructure and Individual data Transport performance by services (age, education level) OD pair and mode Simulation (Outputs) Road network Mobility data Travel times by mode Service quality ( trip sequence, each trip (origin, PT GTFS model Waiting time destination, schedule, purpose, Probability of trip transport mode)) Detour time production / attraction Spatial definition and Operational Performance Average vehicle occupancy resolution Land use data (Grid) Transport demand & Fleet requirements Population supply scenarios Study area boundaries Costs Employment Society (Sustainability) Demand (Scenario specification) Ameneties (POIs) Emissions Grid system definition Private car trips, Building footprint (% modal shift to SM), Congestion Bus trips (% modal shift to SM ) Accessibility indicators Focus group and Parking requirements stated preference analysis Supply (Scenario specification) Private car (allowed: Yes/No) Willingness to shift to SM Bus (preserved: Yes/No) SM mode selection BRT (preserved: Yes/No) Walking & biking (preserved: Yes) Shared-Taxi, Taxi-Bus Rail and Ferry (preserved: Yes) Feeder service to Low Emission Zone (active: rail, ferry or BRT Yes/No)

Agent gent-based d Simula Simulati tion n fra ramewo mework rk Dispatcher Clients Vehicles

Agent gent-based d Simula Simulati tion n fra ramewo mework rk drive to or destination (drivers) pick-up user drop-off user Coordinates, ride taxi User departure time origin Coordinates, arrival time destination ride car assignment drive or walk drop-off carpoolers Shared mode walk from stop preference (carpoolers) walk from stop walk to stop (Heavy PT feeder) travel plan ride bus (updates every 15 minutes) walk from stop Vehicles (destination)

Current m mobilit ility Land use patterns T ransport supply characterisation Mode choice and car ownership CO 2 intensity per inhabitant

Land nd us use e pa patter tterns ns PT service Connectivity PT / PC Highways Heavy PT provision PT travel time City network density infrastructure (seat-km heavy (avg. linear ratio (km/sqkm)* (km / 1000 inhab.) PT / 1 million speed for (trips > inhab.) trips > 1km) ** 1km) Auckland 0.2 0.1 3.7 8.0 2.8 Dublin 0.4 0.07 4.9 6.7 2.7 Helsinki 0.7 0.21 16.2 16.1 1.0 0.5 0.14 6.7 7.9 3.1 Lisbon Lyon 0.8 0.15 9.8 12.1 1.9

T ra rans nspo port s t supply upply character terisati ation Population density Land use mixture Study area size CBD influence City (inhab. / sqkm – total (avg. entropy (total / active) radius* / active surface) index) Auckland 2 233 / 986 582 / 1 318 0.32 17.5 Dublin 6 988 / 1 047 258 / 1 720 0.36 16.8 Helsinki 770 / 639 1 414 / 1 703 0.29 20.6 Lisbon 3 015 / 999 929 / 2 802 0.53 8.9 Lyon 532 / 512 2 518 / 2 616 0.48 12.6 * Highways are all road links with speed greater than 80 km/h. ** It includes 10 minutes penalty in the calculation for each transfer by public transport

Mode de cho hoic ice e and nd car r owner wnership hip 1% 1% 0% 4% 4% 1% 3% 3% 5% 9% 82% 5% 57% 4% 47% 6% 2% 0% 41% 15% 41% 1% 8% 20% 7% 3% 38% 27% 25% 13% 18% 1% 3% 0% 0% 0% 0% 1% 1% 3% 0% Walk Bicycle Bus + BRT Tram + LRT Metro Rail Ferry PC + Heavy PT PC + motorbike Taxi (Auckland) (Dublin) (Helsinki) (Lisbon) (Lyon)

Mode de cho hoic ice e and nd car r owner wnership hip Car GDP per Non-motorised Heavy public Light public Private ownership City capita transport (%) transport (%) transport car (%) (cars / 100 (USD/inhab.) * ** (%) *** **** inhab.) Auckland 54 178 680 14 1 3 82 Dublin 56 971 350 30 5 8 57 Helsinki 49 364 320 32 12 15 41 Lisbon 32 434 217 19 12 20 49 Lyon 32 213 400 40 13 6 41 * includes walking and bicycle. ** includes rail, metro, bus rapid transit (BRT), light rail transit (LRT) and ferry. *** includes bus and tram. **** includes car, taxi and motorcycle, both as a driver and as a passenger.

CO2 2 intens intensit ity per per inha inhabit bitant nt 6.0 3.1 2.5 3.5 2.9 (Auckland) (Dublin) (Helsinki) (Lisbon) (Lyon) kg of CO 2 per inhabitant.day

Urban an p policy t testi sting Impacts Full adoption scenario Factors affecting outcome T esting targeted policies T ransition

Impacts (Full adoption scenario) 2.7 2.1 1.8 1.6 1.5 (Auckland) (Dublin) (Helsinki) (Lisbon) (Lyon) CO2 /inhabitant kg of CO 2 per inhabitant.day

Fact ctors a s affect cting o g outco come me Current modal share Public transport quality Density of the area T rip patterns

Carbon intensity model City layout Transport supply Shared mobility market adoption (land use characteristics and (public transport and road (private car and bus users mobility patterns) provision) adoption) Highways network density Share of users of conventional bus Average trip distance (km) (km/sqkm) * (%) Service provision Case study area size Share of users of high (seat-km heavy PT per 1 million (skm) performance bus (%) inhabitants) Share of remaining car users ** Non-motorised transport (%) (%) Population density (inhab. / sqkm) * High performance is considered either a BRT or buses with a high level of service (BHLS) or bus service with headway lower than 7.5 minutes. The remaining bus is considered conventional. ** This variable measures the resulting car modal share after the adoption of shared mobility by part of the original demand defined in the input scenario.

Carbon intensity model Urban context factor analysis PA1 is characterised by strong public transport provision and low non-motorised Variable PA1 PA2 transport and private car infrastructure Highways network density (km/sqkm) -0.66 0.75 Service provision provision. This factor was designated 1.04 -0.07 (seat-km heavy PT per 1 million inhabitants) “ public transport centred mobility ” Population density (inhab. / sqkm) 0.21 0.77 Non-motorised transport (%) -0.67 0.68 PA2 is explained by strong non-motorised Average trip distance (km) 0.55 -0.68 Case study area size (skm) 0.54 -0.03 mobility in a dense urban context with shorter trips but in presence of good motorway network. This factor was named “ dense urban context ”